# The Cloud Efficiency Playbook | 8 Lessons From PointFive Customers Canonical: https://www.pointfive.co/playbook Eight lessons from engineering teams running PointFive in production: Nubank, PwC, Net Health, Blackhawk, Fanatics, and more. Mature FinOps wasn't the problem. Root cause was. # You don't have a visibility problem. You have a root-cause problem. The Playbook: eight lessons from engineering teams running PointFive in production. [Read the full case studies](https://www.pointfive.co/case-studies) From the field, with - Nubank - Net Health - PwC - Blackhawk Network - Fanatics - Dolby - 10 days to ROI in the Nubank proof of concept - $300K+ AWS savings within months at Dolby - 3,000+ autonomous remediations at Nubank - 200+ waste types triggering across Nubank's AWS ## Visibility wasn't the problem. Root cause was. Every customer started with mature cost reporting. The breakthrough wasn't more data, it was the layer that explains why costs moved. Nubank Homegrown cost transparency platform with full chargeback. Cost Champions in 45+ business units. Could see spend rise, but rarely the reasons. Net Health FinOps tools for budgeting and forecasting at the subscription level. Couldn't identify what was wasted, over-provisioned, or misconfigured. Fanatics Commerce Already reached the 'Run' phase of FinOps maturity. Reporting was embedded. Costs kept rising anyway. ### Net Health: what past cleanups missed Sprawl persisted after earlier cleanup efforts, which missed resources scattered across subscriptions and resource groups, especially orphaned disks and other low-cost line items that rarely trigger urgency but still represent waste and risk. PointFive analyzed what was wasted, underutilized, or misconfigured. ## The money hides where no one is looking. Items too small to flag individually. Too distributed to address centrally. Surfaced and addressed at scale, they add up. - 150+ detached EBS volumes, individually small, $20K a month collectively Dolby - 200+ waste types triggering across Nubank's AWS, continuously Nubank - Orphans Disks and low-cost items scattered across subscriptions, quietly compounding Net Health ## Generic flags get ignored. Context gets fixed. Every opportunity arrives with the same four pieces. Root cause Why this happened, not just what. Cost impact Dollars, not flags. Suggested fix With remediation scripts where they exist. Associated risk So engineers validate before changing. PointFive allows us to quickly and easily get actionable cost savings recommendations in front of our engineers. Fanatics Director of Engineering Fanatics Commerce ## Days, not quarters. When the long tail is surfaced and routed, the math moves fast. - 10 days to ROI: recovering the full annual cost of PointFive's contract during the POC Nubank - $300K+ in AWS savings within months across S3, EBS, EC2, EKS and RDS Dolby - 1% to 3% Net Health hit its Azure savings target, then tripled the goal Net Health ## Measure in recommendations, not dollars. Tie KPIs to dollars saved and engineers fight over the biggest, easiest fixes. The long tail goes untouched. Net Health measures the number of PointFive recommendations completed, including thoughtful dismissals with documented reasoning. Disciplined evaluation, not blind cost-cutting. Outcome: engineers hit quarterly targets a month ahead of schedule. - ### Engineers tackle the long tail, not just easy wins - ### Dismissals with reasoning count as completion - ### Milestone-based: October to November to December targets - ### Performance reviews tied to completion, not appearances ## Automation changes the math. Nubank, storage and databases. A custom pipeline integrates PointFive's GraphQL API into Nubank's internal automation. Dozens of DynamoDB optimizations applied per day with zero engineer involvement. - 3,000+ Autonomous remediations - 2.5x Savings potential vs. manual remediation - Zero Engineer involvement ### The non-obvious bit The pipeline is bidirectional. When access patterns rise again, it reverses the change. DynamoDB usage isn't static, and a one-time migration wouldn't stay optimized. ## AI workloads need a pipeline view. AI workload investigation connects service costs to pipelines, model training, and infrastructure choices. Explore PwC's work on LLM training costs. - 32B Parameter LLM in training - 8 AWS regions mapped end to end - 5 NVIDIA GPU architectures optimized - ### What got mapped - Data preparation and tokenization - GPU training and fine-tuning - SageMaker HyperPod clusters - FSx for Lustre storage tiers - S3 checkpoint distribution across regions - ### What was identified: $9K to $15K a month 11% to 19% cost reduction across snapshot archival, S3 Intelligent-Tiering, data transfer, and instance scheduling. ## The savings are the headline. The operating model is the win. Nubank Cloud efficiency stopped being a centralized FinOps mandate. It became part of engineering's regular work: clear ownership, trusted data, remediation through existing Jira and ServiceNow workflows. Blackhawk Network Optimization shifted from a reporting exercise to an engineering discipline. Teams engage with opportunities as part of their regular work. Net Health A savings program became a repeatable model: cloud efficiency improves when KPIs are clear and the work fits existing engineering workflows. I can confidently say that PointFive supports our daily work by unifying the infrastructure, providing valuable and easily accessible analytical data to support decision-making. Dolby Cloud FinOps Analyst Dolby --- Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.